The moderating influence of device characteristics and usage on user acceptance of smart mobile devices

This study seeks to develop a comprehensive model of consumer acceptance in the context of Smart Mobile Device (SMDs). This paper proposes an adaptation of the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT2) model that can be employed to explain and predict the acceptance of SMDs. Also included in the model are a number of external and new moderating variables that can be used to explain user intentions and subsequent usage behaviour. The model holds that Activity-based Usage and Device Characteristics are posited to moderate the impact of the constructs empirically validated in the UTAUT2 model. Through an important cluster of antecedents the proposed model aims to enhance our understanding of consumer motivations for using SMDs and aid efforts to promote the adoption and diffusion of these devices

Understanding and Predicting the Determinants of Consumers’ Acceptance and Usage of M-commerce Application: Hybrid SEM and Neural Network Approach

In m-commerce, privacy and security are major concerns. Existing research has examined the privacy and relationship, security, and intention to use. However, the determinants of privacy and security in mobile commerce remain largely unexplored. A study based on UTAUT2 and trust examines the factors that influence mobile commerce privacy and security. By using the approach of hybrid SEM/ANN analysis, it is possible to detect non-linear and non-compensatory relationships. According to linear and compensatory models, the absence of one determinant can be compensated for by another. The decision-making process of consumers is actually quite complex, and non-compensatory or linear models tend to simplify it. The sample is collected by using a mobile commerce application in order to gather 890 datasets on mobile commerce consumers. Findings: (1) Two determinants of M-commerce acceptance and use had an explicit and significant positive effect. Security and individual are two of these factors. (2) Privacy concerns have a severe negative impact on M-commerce acceptance and use. (3) Trust is found to partially mediate the effect on behavioral intentions of Security Factors (SCF), Privacy Factors (PRF), and Individual Factors (INF) on m-commerce in Jordan (INTENTION). According to the integrated model, m-commerce offers 71% privacy, security, and trust. Doi: 10.28991/ESJ-2022-06-06-018 Full Text: PD

Assessing the Benefit of Adopting ERP Technology and Practicing Green Supply Chain Management toward Operational Performance: An Evidence from Indonesia

The recent concern on the environmental protection and COVID-19 issue is increasingly affecting the manufacturing industry. This research assessing the benefit of adopting ERP technology and practicing green supply chain management toward operational performance in manufacturing industry. The study is essential to provide insight for the manufacturing industry regarding the consequences and benefits of practicing the green supply chain and adopting ERP technology amid the current constraints of the environmental protection issue and the COVID-19 pandemic. The study has surveyed 122 companies domiciled in Indonesia. Data collection used a questionnaire designed with a seven-point Likert scale. Questionnaire created in Google form, printed and distributed using social media and postal mail. Data analysis used SmartPLS software version 3.0. The result revealed that ERP adoption enables green purchasing, production, distribution, and operational performance. Furthermore, operating performance is directly affected by green purchasing and green production. However, operating performance was not supported by green distribution. In addition, ERP adoption indirectly improves operational performance through green purchasing and green production. But ERP adoption did not affect operational performance through green distribution. This result provides essential insight for the manager in the manufacturing industry that adopting ERP in the era of the COVID-19 pandemic and practicing environmental protection such as green purchasing, green production enhances operational performance. In summary, the result of this study encourages the practitioner to adopt environmental protection in running their business since it benefits the company. While there are very few studies examining the relationship between ERP adoption, green supply chain practices, and operational performance, this study is essential in terms of exploring the mediating role of green supply chain practices on the effect of ERP adoption on operational performance. Thus, these research findings could enrich the current research in the supply chain management context

IS Success Model in E-Learning Context Based on Students\u27 Perceptions

This study utilized the Information Systems Success (ISS) model in examining e-learning systems success. The study was built on the premise that system quality (SQ) and information quality (IQ) influence system use and user satisfaction, which in turn impact system success. A structural equation model (SEM), using LISREL, was used to test the measurement and structural models using a convenience sample of 674 students at a Midwestern university. The results revealed that both system quality and information quality had significant positive impact on user satisfaction and system use. Additionally, the results showed that user satisfaction, compared to system use, had a stronger impact on system success. Implications for educators and researchers are reported

Examining the two-dimensional perceived marketplace influence and the role of financial incentives by SEM and ANN

In recent years, research on sustainable consumption has been particularly relevant, highlighting the importance of the collective over the individual to reduce pollution. This study focuses on the study of the perceived marketplace influence (PMI) concept in its organizational and consumer dimensions, together with the financial incentives that exist in the adoption of electric cars and their effect on green customer engagement. A sample of 382 potential buyers of electric vehicles was obtained. A new hybrid analytical approach was taken structural equation modelling and artificial neural network. The research found the most significant variables affecting purchase intention were financial incentives, followed by PMI Organization and finally PMI Consumer. The results of artificial neural network analysis confirmed all the findings of the structural equation modelling, although the importance of each PMI dimension is different for each technique used. The conclusions point to new business opportunities that can be exploited by companies selling this green technology.Funding for open access charge: Universidad de Granada / CBU

Assessing the benefit of adopting ERP technology and practicing green supply chain management toward operational performance: An evidence from Indonesia

The recent concern on the environmental protection and COVID-19 issue is increasingly affecting the manufacturing industry. This research assessing the benefit of adopting ERP technology and practicing green supply chain management toward operational performance in manufacturing industry. The study is essential to provide insight for the manufacturing industry regarding the consequences and benefits of practicing the green supply chain and adopting ERP technology amid the current constraints of the environmental protection issue and the COVID-19 pandemic. The study has surveyed 122 companies domiciled in Indonesia. Data collection used a questionnaire designed with a seven-point Likert scale. Questionnaire created in Google form, printed and distributed using social media and postal mail. Data analysis used SmartPLS software version 3.0. The result revealed that ERP adoption enables green purchasing, production, distribution, and operational performance. Furthermore, operating performance is directly affected by green purchasing and green production. However, operating performance was not supported by green distribution. In addition, ERP adoption indirectly improves operational performance through green purchasing and green production. But ERP adoption did not affect operational performance through green distribution. This result provides essential insight for the manager in the manufacturing industry that adopting ERP in the era of the COVID-19 pandemic and practicing environmental protection such as green purchasing, green production enhances operational performance. In summary, the result of this study encourages the practitioner to adopt environmental protection in running their business since it benefits the company. While there are very few studies examining the relationship between ERP adoption, green supply chain practices, and operational performance, this study is essential in terms of exploring the mediating role of green supply chain practices on the effect of ERP adoption on operational performance. Thus, these research findings could enrich the current research in the supply chain management context

A Framework to Study Factors Influencing the Acceptance of Information Technology in Yemen Government

Organizations around the world are looking for the development and keep up to date with emerging technology. Thus, they pay more intention to develop their technology infrastructure to improve productivity, effectiveness, or to adopt e-government. However, in reality, not all companies adopt and use effectively, or even use, information technology. And in reality, not all employees in organizations accept, adopt, and use effectively, or even use, information technology. When this happens, there is a gap between the ideal and the reality of the actual usage of information technology. As a result, there is need to study and understand the factors affecting the acceptance of technologies. This study aims to test the success of the technology acceptance model in Yemen culture. In addition, This study aims to investigate the factors influencing the acceptance of technology in Yemen public sector. This study developed a framework based on two theories, TAM 2 and UTAUT. In addition, the study added two important factors of organization culture and government support to the key factors in the theory of technology acceptance in order to provide better understanding for the factors influencing the acceptance of information technology among the individual perceptions. survey questionnaire was distributed to 53 government utilities and 357 cases were used in the analysis. Structural Equition Modeling AMOS 18 was used for the analysis of the proposed model, from a total 14 hypothesis, 11 were supported and three hypothesis were rejected. This study provided empirical evidence for the effects of new technology determinants in the government sector. In particular, it has successfully revealed that organization culture, government support, subjective norm, top management support and information quality are important determinants in influencing the adoption of technologies. The findings confirmed the theory of TAM and showed its potential capability in the Middle East, particularly in Yemen

A PLS-SEM Neural Network Approach for Understanding Cryptocurrency Adoption

© 2013 IEEE. The majority of previous research on new technology acceptance has been conducted with single-step Structural Equation Modeling (SEM) based methods. The primary purpose of the study is to enhance the new technology acceptance based research with the Artificial Neural Network (ANN) method to enable more precise and in-depth research results as compared to the single-step SEM method. This study measures the relation between technology readiness dimension (optimism, innovativeness, discomfort, insecurity) and the technology acceptance (perceived ease of use and perceived usefulness) - and the intention to use cryptocurrency, such as bitcoin. The contribution of this study include the use of a multi-analytical approach by combining Partial Least Squares- Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) analysis. First, PLS-SEM was applied to assess which factor has significant influence toward intention to use cryptocurrency. Second, an ANN was employed to rank the relative influence of the significant predictor variables attained from the PLS-SEM. The findings of the two-step PLS-SEM and ANN approach confirm that the use of ANN further verifies the results obtained by the PLS-SEM analysis. Also, ANN is capable of modelling complex linear and non-linear relationships with high predictive accuracy compared to SEM methods. Also, an Importance-Performance Map Analysis (IPMA) of the PLS-SEM results provides a more specific understanding of each factor's importance-performance